Author ORCID Identifier

Date of Award

Spring 5-12-2023

Degree Type

Capstone Project

Degree Name

Master of Public Health (MPH)


Public Health

First Advisor

Alexander Kirpich

Second Advisor

Ruiyan Luo


The topic analyzed was the demographic, socioeconomic, and health factors that may influence the depression status of elderly Americans aged 60 years or older in 2021. Depression status was identified as being notified of having depression through identifiable depressive symptoms or clinical diagnosis. It is currently defined as a mood disorder that causes a persistent feeling of sadness, loss of interest, and long-term difficulty in day-to-day activities. Elderly depression has been prevalent due to complications regarding issues of wealth, health accessibility, and increased risk of cognitive issues. The dataset is from the 2021 Behavioral Risk Factor Surveillance System (BRFSS), which is composed of telephone interviews in all U.S. states (n = 85,398 depression respondents). Within the dataset, collected variables such as gender, race/ethnicity, marital status, income, education level, and health insurance status were used as model predictors to determine associations within elderly depression (i.e. individuals aged 60 years or older). It was found that all variables, excluding health insurance status, were found to be statistically significant predictors of depression in elderly Americans (p<0.0001). However, through multiple logistic regression, a model containing all selected variables, including health insurance, was found to have the best prediction for depression. Disadvantaged demographic and socioeconomic groups such as being female, never married/separated, lower household income class, and having a low education status were found to increase the likelihood of depression in elderly Americans. Compared to most minorities, being white and non-Hispanic was also found to increase the likelihood of depression. This finding suggests that disparities are present within the American elderly population and that utilization of intervention programs can be targeted toward those at a higher risk for depression.


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